The discovery of accurate molecular and cellular network models will greatly advance our ability to predict the consequences of genetic states on human health.
The Stuart lab uses data-driven approaches to identify and characterize genetic networks, investigate how they've evolved, and then use them to simulate and predict cellular behavior. Our approach is to design computational models and algorithms that integrate high-throughput molecular biology datasets (genomic, epigenomic, and functional genomic) to predict cellular- and organism-level phenotypes. We have a particular focus on elucidating altered signaling pathways in cancer cells that initiate and drive tumorogenesis and are developing models to predict the impact of mutations in human tissue and a patient's response to treatment. Several projects are underway to infer and visualize the activities of genetic systems to shed light on how they function in living cells and tissues.